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Two novel outlier detection approaches based on unsupervised possibilistic and fuzzy clustering
Author(s) -
Zeynel Cebecí,
Çagatay Cebeci,
Yalçın TAHTALI,
Lütfi Bayyurt
Publication year - 2022
Publication title -
peerj computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.927
H-Index - 70
ISSN - 2376-5992
DOI - 10.7717/peerj-cs.1060
Subject(s) - outlier , anomaly detection , cluster analysis , data mining , computer science , pattern recognition (psychology) , identification (biology) , data set , artificial intelligence , data point , set (abstract data type) , botany , biology , programming language

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